title: Hierarchical clustering combining numerical and biological similarities for gene expression data classification.
abstract: High throughput data analysis is a challenging problem due to the vast amount of available data. A major concern is to develop algorithms that provide accurate numerical predictions and biologically relevant results. A wide variety of tools exist in the literature using biological knowledge to evaluate analysis results. Only recently, some works have included biological knowledge inside the analysis process improving the prediction results.
authors.forename: Mattia
authors.initials: M
authors.lastname: Bosio
authors.forename: Philippe
authors.initials: P
authors.lastname: Salembier
authors.forename: Pau
authors.initials: P
authors.lastname: Bellot
authors.forename: Albert
authors.initials: A
authors.lastname: Oliveras-Vergès
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D016208:Databases, Factual; D009010:Monte Carlo Method; D025341:Principal Component Analysis; D059467:Transcriptome